arXiv subjects

Lilianne Nakazono

Publications and source records attributed to Lilianne Nakazono.

8 recordsLinked to original sources

arXiv2026

First tomographic measurements of the angular clustering and bias of photometric quasars from S-PLUS

We investigate the quasar clustering in the QuCatS photometric catalog, constructed from the fourth data release of the Southern Photometric Local Universe Survey (S-PLUS). The quasar sample for this study consists of $23,402$ quasars, spanning the redshift interval $1.1 \leq z_{\rm phot} \leq 2.6$, which we divided into four bins for our tomographic analyses. In each bin, we measured the two-point angular correlation function and compared it with theoretical predictions for the clustering of dark matter in the flat-$Λ$CDM cosmological model. We then estimate the effective linear bias in each bin that best fits the data, obtaining $b_{Q}(z_{\rm eff}=1.26)=2.17^{+0.30}_{-0.35}$, $b_{Q}(z_{\rm eff}=1.63)=2.67^{+0.36}_{-0.42}$, $b_{Q}(z_{\rm eff}=2.04)=3.29^{+0.52}_{-0.62}$, and $b_{Q}(z_{\rm eff}=2.38)=4.05^{+0.71}_{-0.86}$. These measurements are consistent with previous analyses in the literature. Moreover, the evolution of the bias agrees well with the $b(z)$ parameterization proposed by \cite{laurent2017}. Our measurements constitute the first cosmological study of the tomographic clustering of photometric quasars provided by the S-PLUS dataset, contributing to the mapping of the evolution of linear bias and paving the way for future analyses of data releases with larger datasets. In addition, our study also serves as a consistency test for the calibration procedure of the photometric redshift probability distributions of the quasars in the QuCatS catalog.

astro-ph.CO↗

arXiv2026

Tabular foundation models for the estimation of probabilistic quasar photometric redshifts in S-PLUS

We assess whether tabular foundation models can be used as off-the-shelf probabilistic photometric-redshift estimators for quasars in the 12-band S-PLUS DR6 survey, where colour-redshift degeneracies produce multi-modal posteriors and spectroscopic training sets are shifted relative to the photometric population. TabPFN 2.5, RealTabPFN 2.5, and TabICL are benchmarked against eight task-specific baselines, including linear conditional Gaussians, FlexZBoost, mixture-density networks, normalising flows, random forests, and gradient-boosted trees, with training sets from 500 to 121,626 quasars, using both density and point-prediction metrics, together with importance-weighted scores that approximate deployment on the photometric target sample. TabPFN 2.5 is best or statistically tied for best on all metrics except the unweighted CDE loss, on which the normalising flow is statistically tied and attains the lowest mean value; its largest gains occur for small training sets and in difficult regimes (very bright and faint sources, high redshift), while retaining near-nominal calibration under covariate shift. Its main practical cost is inference: with frozen weights, large support and target catalogues require substantial GPU/accelerator memory, and full-catalogue deployment may need support-set subsampling or distillation. SHAP attributions identify WISE W1/W2 as the strongest individual predictors, with UV and optical bands offering non-negligible refinements. We conclude that TabPFN 2.5 is a strong default for probabilistic quasar photo-z estimation, particularly when training data are limited or when calibration under covariate shift is critical.

astro-ph.IM↗

arXiv2026

The S-PLUS Fifth Data-Release: Over 4500 square degrees of the Southern Sky and a multicolor view of the Hydra and Antlia galaxy clusters

We present the 5th data release (DR5) of the Southern Photometric Local Universe Survey (S-PLUS), covering 4592 square degrees across 2491 fields. Observations were conducted with the T80-South, a Brazilian robotic telescope equipped with the Javalambre 12-filter system, containing five broad- and seven narrowband filters. Data products feature FITS images and extensive catalogs containing fluxes, magnitudes, and shape parameters for over 113 million detections. In addition, several value-added catalogs are provided, offering photometric redshifts (photo-zs), object classifications, masks, and extinction coefficients. For the first time, this release includes coverage of 110 square degrees along the Galactic disk, facilitating new research into Galactic structure and stellar populations. The release also provides full coverage of the Hydra Supercluster and numerous other nearby clusters with improved data reduction and calibration, enhancing photo-z accuracy, which is vital for large-scale structure studies. A preliminary analysis of the Hydra and Antlia galaxy clusters up to $5 \times R_{200}$ yields an updated catalog of 1706 cluster members based on both spectroscopic and high-quality photo-zs. Our photometric data shows that both clusters have a similar proportion of galaxies with an H$α$ excess relative to their clustercentric distance, though Hydra has a higher fraction near its center. Additionally, the spatial distribution of all objects in our sample highlights a bridge connecting both clusters. We verify that S-PLUS DR5 provides a solid foundation for future scientific investigations, ranging from Solar System studies to Cosmology.

astro-ph.GA↗

arXiv2026

SAGUI: SED-based Segmentation of Multi-band Galaxy Images -- Application to JADES in GOODS-South

We present sagui, a modular framework for the analysis of multi-band imaging data in spatially resolved galaxies, with synergies to integral-field spectroscopy (IFS). Building on the spectro-spatial paradigm introduced by capivara for IFS data, sagui extends this approach to imaging datasets, enabling a coherent, pixel-level treatment of spatial and spectral information across multiple bands. The method follows a two-stage strategy: a starlet-based decomposition is first used to identify and mask spatial structures across multiple scales while suppressing noise, and a spectral-similarity analysis then partitions the image into coherent pixel groups that preserve spectral consistency. In addition to compact and high-contrast structures, the framework incorporates a dedicated statistical treatment, based on a copula transform, to identify and recover faint, diffuse low-surface-brightness components. We demonstrate the method across a diverse range of galaxy morphologies, highlighting its ability to characterize complex spatial structures, including clumps, bars, interacting systems, and low-surface-brightness features. As a case study, we apply it to eleven morphologically diverse galaxies from the James Webb Space Telescope Advanced Deep Extragalactic Survey in the GOODS--South field. sagui is released under an MIT license and is available at https://rafaelsdesouza.github.io/sagui/.

astro-ph.IM↗

arXiv2026

AstroInspect: a web-based system to organize, assess, and visually inspect astronomical objects

The rapid growth of imaging and spectroscopic surveys has intensified the need for efficient tools that support visual inspection, a practice that remains essential for tasks such as classification, catalog refinement, and validation of automated methods. Existing solutions, however, often require the use of multiple platforms and complex workflows to integrate heterogeneous data. To address this challenge, we present the first release of the AstroInspect (https://astroinspect.github.io), a web-based system which ensures seamless access to several astronomical resources. The system provides an intuitive graphical user interface (GUI) through which users can upload catalogs of objects defined by celestial coordinates. AstroInspect automatically enriches these catalogs with complementary information, including imaging, spectroscopic, and photometric data retrieved in real time from surveys such as the Sloan Digital Sky Survey (SDSS), the Legacy Surveys (LS), and the Southern Photometric Local Universe Survey (S-PLUS). As an example of its scientific utility, we used AstroInspect to identify H$α$ emission-line galaxies within a 7 deg radius in the direction of the Hydra I cluster (also known as Abell 1060) by visual inspection. Using a candidate set of 981 galaxies selected from S-PLUS photometric data, we produced a catalog of 80 galaxies with confirmed H$α$ emission. These results highlight the potential of AstroInspect to support efficient visual inspection workflows.

astro-ph.IM↗

arXiv2025

AT2022zod: An Unusual Tidal Disruption Event in an Elliptical Galaxy at Redshift 0.11

Tidal Disruption Events (TDEs) have long been hypothesized as valuable indicators of black holes, offering insight into their demographics and behaviour out to high redshift. TDEs have also enabled the discovery of a few Massive Black Holes (MBHs) with inferred masses of $10^4$--$10^6\,M_\odot$, often associated with the nuclei of dwarf galaxies or ultra-compact dwarf galaxies (UCDs). Here we present AT2022zod, an extreme and short-lived optical flare in an elliptical galaxy at z=0.11, residing within 3kpc of the galaxy's centre. Its luminosity and ~30-day duration make it unlikely to have originated from the host galaxy's central supermassive black hole (SMBH), which estimate to have a mass around $10^8\,M_\odot$. Assuming that the emission mechanism is consistent with known observed TDEs, we find that such a rapidly evolving transient could either be produced by a MBH in the intermediate-mass range or, alternatively, result from the tidal disruption of a star on a non-parabolic orbit around the central SMBH. We suggest that the most plausible origin for AT2022zod is the tidal disruption of a star by a MBH embedded in a UCD. As the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, we propose that AT2022zod serves as an important event for refining search strategies and characterization techniques for intermediate-mass black holes.

astro-ph.HE↗

arXiv2024

The Fourth S-PLUS Data Release: 12-filter photometry covering $\sim3000$ square degrees in the southern hemisphere

The Southern Photometric Local Universe Survey (S-PLUS) is a project to map $\sim9300$ sq deg of the sky using twelve bands (seven narrow and five broadbands). Observations are performed with the T80-South telescope, a robotic telescope located at the Cerro Tololo Observatory in Chile. The survey footprint consists of several large contiguous areas, including fields at high and low galactic latitudes, and towards the Magellanic Clouds. S-PLUS uses fixed exposure times to reach point source depths of about $21$ mag in the $griz$ and $20$ mag in the $u$ and the narrow filters. This paper describes the S-PLUS Data Release 4 (DR4), which includes calibrated images and derived catalogues for over 3000 sq deg, covering the aforementioned area. The catalogues provide multi-band photometry performed with the tools \texttt{DoPHOT} and \texttt{SExtractor} -- point spread function (\PSF) and aperture photometry, respectively. In addition to the characterization, we also present the scientific potential of the data. We use statistical tools to present and compare the photometry obtained through different methods. Overall we find good agreement between the different methods, with a slight systematic offset of 0.05\,mag between our \PSF and aperture photometry. We show that the astrometry accuracy is equivalent to that obtained in previous S-PLUS data releases, even in very crowded fields where photometric extraction is challenging. The depths of main survey (MS) photometry for a minimum signal-to-noise ratio $S/N = 3$ reach from $\sim19.5$ for the bluer bands to $\sim21.5$ mag on the red. The range of magnitudes over which accurate \PSF photometry is obtained is shallower, reaching $\sim19$ to $\sim20.5$ mag depending on the filter. Based on these photometric data, we provide star-galaxy-quasar classification and photometric redshift for millions of objects.

astro-ph.GA↗

arXiv2022

Panel Discussion: Practical Problem Solving for Machine Learning

Machine Learning is a powerful tool for astrophysicists, which has already had significant uptake in the community. But there remain some barriers to entry, relating to proper understanding, the difficulty of interpretability, and the lack of cohesive training. In this discussion session we addressed some of these questions, and suggest how the field may move forward.

astro-ph.IM↗